DP-GEN (Deep Potential GENerator) is a software written in Python, delicately designed to generate a deep learning based model of interatomic potential energy and force field. DP-GEN is dependent on DeePMD-kit. With highly scalable interface with common softwares for molecular simulation, DP-GEN is capable to automatically prepare scripts and maintain job queues on HPC machines (High Performance Cluster) and analyze results.
If you use this software in any publication, please cite:
Yuzhi Zhang, Haidi Wang, Weijie Chen, Jinzhe Zeng, Linfeng Zhang, Han Wang, and Weinan E, DP-GEN: A concurrent learning platform for the generation of reliable deep learning based potential energy models, Computer Physics Communications, 2020, 253, 107206.
DP-GEN only supports Python 3.9 and above. You can setup a conda/pip environment, and then use one of the following methods to install DP-GEN:
pip install dpgen
conda install -c conda-forge dpgen
git clone https://github.com/deepmodeling/dpgen && pip install ./dpgen
To test if the installation is successful, you may execute
dpgen -h
DP-GEN contains the following workflows:
dpgen run
: Main process of Deep Potential Generator.dpgen init_bulk
: Generating initial data for bulk systems.dpgen init_surf
: Generating initial data for surface systems.dpgen init_reaction
: Generating initial data for reactive systems.dpgen simplify
: Reducing the amount of existing dataset.dpgen autotest
: Autotest for Deep Potential.For detailed usage and parameters, read DP-GEN documentation.
The project dpgen is licensed under GNU LGPLv3.0.
DP-GEN is maintained by DeepModeling's developers. Contributors are always welcome.